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Record W2996105517

The Education and Integration of Immigrant Children in Ontario: A Content Analysis of Policy Documents Guiding Schools’ Response to the Needs of Immigrant Students

2019· article· en· W2996105517 on OpenAlexvenueaboutno aff
Carla Camila Lara, Louis Volante

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationDiversification (marketing strategy)Christian ministryPolitical scienceEconomic growthPublic relationsPopulationPublic policyPedagogySociologyBusinessEconomicsMarketing
DOInot available

Abstract

fetched live from OpenAlex

Given the rise and diversification of the immigrant student population within Canadian school systems,the establishment of policies that support immigrant pupils’ transition and integration has become ofpressing concern for policymakers. Following our multi-dimensional support model, this study examinedthe extent to which Ontario’s provincial education policies, guidelines, and strategies respond to the needsof immigrant students within the K-12 public education system. For the most part, the current analysisindicated that the ministry has established the necessary educational support measures to integrate immigrant students. However, our findings also suggest that this group of students warrants a stand-alonepolicy document to comprehensively address all of their unique needs. Moreover, this study underscoresthe importance of greater policy coherence and direction within Ontario, as well as the ongoing role thatevidenced-based research should serve in the development and refinement of existing policies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0070.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.358
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2019
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Educational Administration and PolicySame topicEducation and experiences of immigrants and refugeesFrench-language works237,207